In this session, we explore how unlocking data, real-time analytics, and AI-powered solutions can drive sustainable growth in manufacturing. We will focus on how compressed air systems can serve as a starting point to scale energy efficiency, predictive maintenance, and continuous machine improvement. Through practical use cases, we will demonstrate how deploying sensors and leveraging real-time analytics in pneumatic systems can effectively monitor conditions and detect anomalies. A key opportunity lies in compressed air, which in many facilities can account for up to 30% of electricity consumption, with as much as one-third wasted due to leaks and inefficiencies. This not only reduces energy efficiency but also increases emissions, complicating efforts to meet reduction targets. With 75% of companies relying on manual leak detection—with annual costs exceeding thousands of dollars per machine—automating this process presents a significant advantage in early leak detection and cost savings, ultimately advancing sustainability goals.